System and method to allocate resources in service organizations with non-linear workflows

ABSTRACT

A method can include determining a number of cases received (e.g., a case load), a number of cases processed (e.g., a case rate), and dividing the case load by the case rate. The resource demand can be compared to a resource allocation, and the resource allocation can be changed based upon the resource demand. A information handling system can include a processor and a memory. The memory can have code stored therein, wherein the code can include instructions, which, when executed by the processor, allows the information handling system to perform part or substantially all of the method.

FIELD OF THE DISCLOSURE

This disclosure relates generally to operating a service organization,and relates more particularly to allocating resources in a serviceorganization.

BACKGROUND

As the value and use of information continues to increase, individualsand businesses seek additional ways to process and store information.One option is an information handling system. An information handlingsystem generally processes, compiles, stores, and/or communicatesinformation or data for business, personal, or other purposes. Becausetechnology and information handling needs and requirements can varybetween different applications, information handling systems can alsovary regarding what information is handled, how the information ishandled, how much information is processed, stored, or communicated, andhow quickly and efficiently the information can be processed, stored, orcommunicated. The variations in information handling systems allow forinformation handling systems to be general or configured for a specificuser or specific use such as financial transaction processing, airlinereservations, enterprise data storage, or global communications. Inaddition, information handling systems can include a variety of hardwareand software resources that can be configured to process, store, andcommunicate information and can include one or more computer systems,data storage systems, and networking systems.

As business markets expand for products and services, the need for abusiness to respond to requests for customer service also increases.Many businesses use a combination of web-based services such asfrequently-asked-question (FAQ) web pages, customer service databases,and e-mail based and live support services, and telephone-based servicesincluding interactive voice response (IVR) systems and live supportservices. Businesses are faced with the task of allocating resourcesbetween these services to adequately meet the increasing number ofservice requests. In allocating resources, businesses can makeassumptions as to the nature and duration of service requests, and howservice requests are processed. For example, a business can assume thatservice requests are handled in a first-in-first-out queue, or that aservice request will be processed in a set amount of time. If theassumptions are incorrect, the business can allocate resourcesincorrectly, leading to underutilized resources or to increased responsetimes.

BRIEF DESCRIPTION OF THE DRAWINGS

It will be appreciated that for simplicity and clarity of illustration,elements illustrated in the Figures have not necessarily been drawn toscale. For example, the dimensions of some of the elements areexaggerated relative to other elements. Embodiments incorporatingteachings of the present disclosure are illustrated and described withrespect to the drawings presented herein, in which:

FIG. 1 is a functional block diagram of a customer service organization

FIGS. 2-4 are diagrams illustrating an exemplary function of a customerservice organization where the workflow in the customer serviceorganization is linear;

FIGS. 5-6 are diagrams illustrating an exemplary function of thecustomer service organization of FIG. 1 where the workflow in thecustomer service organization is non-linear;

FIG. 7 is an illustration of service requests in the customer serviceorganization of FIG. 1;

FIG. 8 is a flow chart illustrating a method of allocating resources ina service organization; and

FIG. 9 is a functional block diagram illustrating an exemplaryembodiment of an information handling system.

The use of the same reference symbols in different drawings indicatessimilar or identical items.

DETAILED DESCRIPTION OF DRAWINGS

The following description in combination with the Figures is provided toassist in understanding the teachings disclosed herein. The followingdiscussion will focus on specific implementations and embodiments of theteachings. This focus is provided to assist in describing the teachings,and should not be interpreted as a limitation on the scope orapplicability of the teachings. However, other teachings can certainlybe used in this application. The teachings can also be used in otherapplications, and with several different types of architectures, such asdistributed computing architectures, client/server architectures, ormiddleware server architectures and associated resources.

As used herein, the terms “comprises,” “comprising,” “includes, ”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of features is notnecessarily limited only to those features, but can include otherfeatures not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive-or and not to an exclusive-or. For example,a condition A or B is satisfied by any one of the following: A is true(or present) and B is false (or not present), A is false (or notpresent) and B is true (or present), and both A and B are true (orpresent).

Also, the use of “a” or “an” is employed to describe elements andresources described herein. This is done merely for convenience, and togive a general sense of the scope of the invention. This descriptionshould be read to include one, or at least one, and the singular alsoincludes the plural, or vice versa, unless it is clear that it is meantotherwise. For example, when a single device is described herein, morethan one device can be used in place of a single device. Similarly,where more than one device is described herein, a single device can besubstituted for that one device.

Unless otherwise defined, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention belongs. Although methods and materialssimilar or equivalent to those described herein can be used in thepractice or testing of embodiments of the present invention, suitablemethods and materials are described below. All publications, patentapplications, patents, and other references mentioned herein areincorporated by reference in their entirety, unless a particular passageis cited. In case of conflict, the present specification, includingdefinitions, will control. In addition, the materials, methods, andexamples are illustrative only, and not intended to be limiting.

To the extent not described herein, many details regarding specificmaterials, processing acts, and circuits are conventional, and can befound in textbooks and other sources within the computing, electronics,and software arts.

A customer service organization provides customer service to a customerbase. In a particular embodiment, the customer service organizationrepresents a service organization within a larger business structure. Inone example, a computer manufacturer can include a service departmentthat handles the complaints or problems encountered by owners oroperators of the computer manufacturer's products (e.g., the customerbase). In another example, a service company, such as a tax preparationcompany, or a provider of janitorial services can include a servicedepartment that schedules services or responds to queries by present orprospective customers. In another embodiment, the customer serviceorganization represents a separate service company. For example, thecomputer manufacturer, the tax preparation company, or the janitorialservice company can contract at least a portion of the service functionsto an outside customer service provider, such as a call center. Inanother embodiment, the service organization includes a combination ofinternal and outside customer service support capabilities.

The customer service organization can provide a variety of channels forthe customer base to gain access to the customer service. For example,the customer service organization can provide personal service in theform of a service center where a particular customer can go to obtainservice, or in the form of mobile service personnel who can go to thecustomer location to provide the service. In another example, thecustomer service organization can provide web-based access to customerservice resources such as a frequently-asked-question (FAQ) web page, acustomer service database, e-mail-based or chat-based live support, orother web based access. Further, the customer service organization canprovide telephone-based services such as an interactive voice response(IVR) system or live support services. In another embodiment, thecustomer service organization can provide a combination of personalservice, web-based service, and telephone-based service.

The resources that the customer service organization uses to meet thedemand for service from the customer base can include network-based andtelephone-based switching equipment to direct service requests to theappropriate source of customer service, personnel (e.g., humanresources, or headcount to staff call centers, handle service centerrequests, and make on-site service calls), and computing equipment(e.g., servers for web-based or IVR service requests). In some cases,the resources can be suitable to handle service requests from variousrequest channels. For example, a service technician can be respond toservice center calls, on-site service, or web-based or IVR servicerequests. Further, a server allocated to handle IVR service requests canbe reallocated to handle web-based service requests. Thus the customerservice organization can manage the resources to meet changing demandsfor service.

The customer service organization can provide services to the customerbase through a variety of service arrangements. In one embodiment, thecustomer service organization provides free service to the customerbase. In another embodiment, the customer service organization chargesthe customer base for service. In yet another embodiment, a combinationof free service and fee-based service is provided. For example,customers with products that are under a warranty can receive servicefree of charge, while customers with products that are not under awarranty can have to pay a fee for service. In another example, thecustomer service organization can provide web-based access to an FAQpage or a customer service database for free, but charge to speak to aservice representative.

FIG. 1 illustrates an embodiment of a customer service organization 100that includes a customer base 110, a service router 120, a personalservice network 130, and an automated service network 140. Customer base110 includes a customer service unit 112, and one or more additionalcustomer service units 114. Customer service units 112 and 114 canrepresent products and their owners, entities with service contracts,members of an at-large population, or other entities or individuals in aposition to use the services provided by customer service organization.Service router 120 includes a personal service queue 122, and anautomated service queue 124. Service router 120 receives servicerequests from customer service units 112 and 114 and routes the servicerequests to either personal service queue 122 or automated service queue124, based upon whether or not the service request is for personalservice or for web-based or IVR service.

Personal service network 130 includes an operator resource 132, and oneor more additional operator resources 134. Operator resources 132 and134 can represent a person who provides service in response to servicesrequests, and can include a technician, an operator, a phone-bankvolunteer, or another provider of service support. Similarly, automatedservice network 140 includes a server resource 142, and one or moreadditional server resources 144. Server resources 142 and 144 canrepresent a server farm or other information processing resource capableof providing web-based services or IVR services.

Service router 120 determines the type of service request being receivedfrom customer service units 112 and 114. Service router 120 also tracksthe availability of operator resources 132 and 134 and server resources142 and 144 to determine if the appropriate resource 132, 134, 142, or144 is available to handle the service request. If no resource 132, 134,142, or 144 is available for the particular type of service request,then service router 120 holds onto the service request until anappropriate resource 132, 134, 142, or 144 becomes available. In aparticular embodiment, service router 120 can hold personal servicerequests in personal service queue 122, and can hold automated servicerequests in automated service queue 124.

If a service request is for personal service, service router 120 routesthe service request to the back of personal service queue 122. Whenoperator resource 132 or 134 becomes available to handle the servicerequest, service router 120 forwards the service request at the front ofpersonal service queue 122 to the available operator resource 132 or 134to process the service request. Likewise, if a service request is forautomated service, service router 120 routes the service request to theback of automated service queue 124. When a server resource 142 or 144becomes available to handle the service request, service router 120forwards the service request at the front of automated service queue 124to the available server resource 142 or 144 to process the servicerequest.

In another embodiment (not illustrated), service router 120 includes asingle queue that receives both personal service requests and automatedservice requests. When an operator resource 132 or 134 becomes availableto handle a service request, service router 120 forwards the personalservice request that is closest to the front of the queue to theavailable operator resource 132 or 134 to process the personal servicerequest. Likewise, when a server resource 142 or 144 becomes availableto handle a service request, service router 120 forwards the automatedservice request that is closest to the front of the queue to theavailable server resource 142 or 144 to process the personal servicerequest

In a particular embodiment of customer service organization 100, any oneor more of resources 132, 134, 142, and 144 can be used one time inprocessing a particular service request. That is, the service requestwill not be handled in more than one incident. For example, a first callto a service center can be sufficient to resolve the particular servicerequest, without any subsequent use of resources 132, 134, 142, or 144.In this embodiment, the workflow performed by customer serviceorganization 100 is termed a linear workflow. FIGS. 2-4 illustrate thefunction of a customer service organization similar to customer serviceorganization 100 where the workflow is linear. Service requests that arereceived by a service router similar to service router 120 areillustrated under a single request block 210. Service requests that arein queue are illustrated under a queue block 230, and service requeststhat have been routed to a resource to be processed are illustratedunder a resource block 240.

FIG. 2 illustrates an embodiment of the customer service organizationwhere the number of service requests received in a given amount of timeis substantially equal to the number of requests that can be processedby the resources in the given amount of time. The lead time is theamount of time a particular service request waits in the queue beforebeing processed. In this embodiment, the lead time remains substantiallyconstant, and the customer service organization is said to be balanced.

FIG. 3 illustrates an embodiment of the customer service organizationwhere the number of service requests received in a given amount of timeis greater than the number of requests that can be processed by theresources in the given amount of time. In this embodiment, the lead timewill increase over time, so the customer service organization is said tobe unbalanced. In order to regain balance, additional resources can beallocated to processing service requests. FIG. 4 illustrates anotherembodiment of the customer service organization where the number ofservice requests received in a given amount of time is less than thenumber of requests that can be processed by the resources in the givenamount of time. In this unbalanced embodiment, the lead time willdecrease over time, and resources can be reallocated to another purpose,instead of to processing service requests.

In another embodiment of customer service organization 100, any one ormore of resources 132, 134, 142, and 144 can be used more than one timein order to fully process a particular service request. That is, theservice request will be handled in more than one incident. Any one ormore of resources 132, 134, 142 or 144 can be used more than one timebecause the outcome of a particular processing step in processing theservice request could be uncertain, and further processing may depend ona response from a customer. For example, a technical support operationcan respond to a service request with a diagnostic flow that takes timefor the customer to implement and obtain diagnostic results.Alternatively, one or more of resources 132, 134, 142 or 144 can be usedmore than one time because a processing step takes time to complete. Forexample, a business can have on-line sales and marketing and be able toprocess orders, but the business may also request signed originaldocuments before completing a customer order. Also, any one or more ofresources 132, 134, 142 or 144 can be used more than one time because aprocessing step is not completed by the customer. For example, acustomer can partially complete an on-line form and save the form forcompletion at a later time. In each of the foregoing situations, theworkflow performed by customer service organization 100 is termed anon-linear workflow. In a non-linear workflow, the resource 132, 134,142 or 144 that started processing the service request can work onprocessing another service request until the next processing incident ofthe prior service request is received. In a particular embodiment, whenthe following processing incident is received, the same resource 132,134, 142 or 144 that started processing the service request can processthe following processing incident. In another embodiment, when thefollowing processing incident is received, a different resource 132,134, 142 or 144 than the resource 132, 134, 142, or 144 that startedprocessing the service request can process the following processingincident.

FIGS. 5-6 illustrate the function of a customer service organizationsimilar to customer service organization 100 where the workflow isnon-linear. New service requests received by a service router similar toservice router 120 are illustrated under a request block 510. Subsequentincidents of a service request that was previously processed by aresource are illustrated under an incident block 520. Service requeststhat are in queue are illustrated under a queue block 530, and servicerequests that have been routed to a resource to be processed areillustrated under a resource block 540.

In a first timeframe 550, illustrated in FIG. 5, a new service request Mis received from customer base 110, and service router 120, determiningthat there are no resources available to process service request M,places service request M at the back of the queue behind servicerequests L and K. When a resource becomes available to process a servicerequest, service router 120 forwards service request K to the resourceto be processed. In timeframe 550, the lead time is two service requestslong. In a following timeframe 552, a second incident of service requestK, labeled K₂, is received. For example, a customer can provide atechnical service center with diagnostic results from a diagnostic flowreceived during an earlier incident of a service request. Service router120 places service request K₂ at the back of the queue behind servicerequest M and L. Also, a new service request N is received from customerbase 110, and service router 120 places service request N at the back ofthe queue behind service requests K₂, M, and L. When a resource becomesavailable to process a service request, service router 120 forwardsservice request L to the resource to be processed. Thus, because of theaddition of the second incident of service request K₂ to the queue, thelead time has grown to three service requests long in timeframe 552. Inanother following timeframe 554, a new service request O is receivedfrom customer base 110, and service router 120 places service request Oat the back of the queue behind service requests N, K₂, and M. When aresource becomes available to process a service request, service router120 forwards service request M to the resource to be processed. Thus, intimeframe 554 the lead time remains three service requests long.

In another following timeframe 556, illustrated in FIG. 6, a new servicerequest P is received from customer base 110, and service router 120places service request P at the back of the queue behind servicerequests O, N, and K₂. When a resource becomes available to process aservice request, service router 120 forwards service request K₂ to theresource to be processed. However, because service request K₂ is asecond incident of service request K, the resource can spend timereviewing the processing completed in the previous incident of servicerequest K, before being able to complete the processing of servicerequest K₂. Thus, in timeframe 556, the lead time remains three servicerequests long, but the processing of service request K₂ is notcompleted. In another following timeframe 558, a new service request Qis received from customer base 110, and service router 120 placesservice request Q at the back of the queue behind service requests P, O,N, and K₂. The resource which began processing service request K₂ intimeframe 556 continues processing service request K₂ in timeframe 558.Thus, because of the additional processing performed on service requestK₂, the lead time has grown to four service requests long in timeframe558.

Notice that the lead time starts out at two service requests long intimeframe 550, and grows to four service requests long in timeframe 558.Thus, as illustrated in FIGS. 5-6, customer service organization 100 isunbalanced due to the non-linear workflow. As in the unbalanced case oflinear workflow, illustrated in FIG. 4, additional resources can beallocated to processing service requests to improve the balance ofcustomer service organization 100. Also, in a particular embodiment (notillustrated), service router 120 can place subsequent incidents of aservice request at the front of the queue. In another embodiment (notillustrated), service requests can be assigned a priority. When a newservice request or a subsequent incident of a service request isreceived, service router 120 can place the service request in the queuein front of service requests with a lower priority and behind servicerequests with a higher priority.

In order to better balance customer service organization 100, theoperator of customer service organization 100 can reallocate operatorresources 132 and 134 or reallocate server resources 142 and 144 fromone function to another. For example, to meet a rising demand forservice, a product warranty center can add to its headcount oftechnicians to respond to service requests. In another example, inresponse to a lower demand for service, a business can reallocateservers that are dedicated to an IVR system to other business purposes.Thus, the operator of customer service organization 100 can try topredict a more balanced allocation of resources based upon historicaldata and current trends. For example, the operator can measure thenumber of service requests received, the rate at which service requestsare received, the growth or decline in the rate, or other measurementsof expected demand for service. Also, the operator can measure thenumber of resources, the efficiency of each resource, the rate at whichthe resources can process the service requests, or other measures ofproductivity of customer service organization 100.

In a particular embodiment, a customer service organization is inbalance when:

R_(in)=R_(out)   (Equation 1)

where R_(in) is the rate at which service requests are received andR_(out) is the rate at which service requests are processed. R_(in) andR_(out) can be in units of service requests per time, where thetimeframe is chosen to be appropriate to the particular customer serviceorganization. When the customer service organization has multipleresources:

R _(out) =N×R _(resource)   (Equation 2)

where N is the number of resources in the customer service organization,and R_(resource) is the rate at which a resource can process servicerequests. Thus the number of resources needed in the customer serviceorganization is given as:

$\begin{matrix}{N = \frac{R_{in}}{R_{resource}}} & \left( {{Equation}\mspace{14mu} 3} \right)\end{matrix}$

In some cases, R_(resource) is not easily measured. However, measuringthe amount of time a resource spends processing a service request can beeasier. In general, the amount of time a resource spends processing aservice request can be give as:

W=W _(A) +W _(OH)   (Equation 4)

where W is the amount of time per service request a resource spends toprocess a service request, W_(A) is the time per service request spentactually processing the service request, and W_(OH) is the time perservice request that is overhead.

FIG. 7 illustrates an embodiment of service requests in customer serviceorganization 100. In this embodiment, the resource is an operatorresource 132 or 134. A new service request 710 and a repeat incident 720are illustrated. New service request 710 includes a time to list servicerequests 712, a time to open the service request 714, a time to evaluatethe service request 716, and a time to process the service request 718.The sum of the times to list service requests 712, to open the servicerequest 714, and to evaluate the service request 716 is the overheadW_(OH) for new service request 710, while the time to process theservice request 718 is the time actually spent processing W_(A) for newservice request 710. Likewise, repeat incident 720 includes a time tolist incidents 722, a time to open the repeat incident 724, a time toevaluate the repeat incident 726, and a time to process the repeatincident 728. The sum of the times to list incidents 722, to open therepeat incident 724, and to evaluate the repeat incident 726 is theoverhead W_(OH) for repeat incident 720, while the time to process therepeat incident 728 is the time actually spent processing W_(A) forrepeat incident 720. Thus, for a new service request:

W_(OH) L+0+E   (Equation 5)

where L is the time to list service requests, O is the time to open theservice request, and E is the time to evaluate the service request. Or,more generally:

W _(OH) =I(L+O+E)   (Equation 6)

where I is the number of incidents to fully process the service request,and therefore:

W=W _(A) +I(L+O+E)   (Equation 7)

Not that ideally the rate at which a resource can process servicerequests R_(resource) is the reciprocal of the amount of time perservice request a resource spends to process a service request W, or:

$\begin{matrix}{R_{resource} = \frac{1}{W}} & \left( {{Equation}\mspace{14mu} 8} \right)\end{matrix}$

However, in some situations resources cannot be dedicated to processingservice requests full time. For example, with human resources, some ofthe work time can be dedicated to breaks, meetings, training, or otheractivities which reduce the amount of time available to process servicerequest. Further, a person in the customer service organization may beonly partially allocated to the task of processing service requests.Likewise, with processing resources, a portion of the processingcapacity can be allocated to tasks other than processing servicerequests. For example, a server may require maintenance and repair, ormay be allocated to other processing functions within the customerservice organization Thus, the rate at which a resource can processservice requests R_(resource) can be reduced by an efficiency factor,such that:

$\begin{matrix}{R_{resources} = \frac{E}{W}} & \left( {{Equation}\mspace{14mu} 9} \right)\end{matrix}$

where E is the efficiency factor. E can be given as:

$\begin{matrix}{E = \frac{T_{A}}{D}} & \left( {{Equation}\mspace{14mu} 10} \right)\end{matrix}$

where T_(A) is the amount of time available to process service requests,and D is the total amount of time. The total amount of time D can dependon whether the resource is an operator resource 132 or 134, or a serverresource 142 or 144. For example, when dealing with operator resources132 and 134, the total amount of time D is typically on the order of 8hours per day, while the total amount of time D is typically on theorder of 24 hours per day for server resources 142 and 144.

Therefore, substituting equations 7 and 10 into equation 9 yields:

$\begin{matrix}{R_{resources} = \frac{T_{A}}{D\left( {W_{A} + {I\left( {L + O + E} \right)}} \right)}} & \left( {{Equation}\mspace{14mu} 11} \right)\end{matrix}$

Finally, substituting equation 11 into equation 3 yields:

$\begin{matrix}{{N = {\frac{D}{T_{A}} \times {R_{in}\left( {W_{A} + {I\left( {L + O + E} \right)}} \right)}}}{{or}\text{:}}} & \left( {{Equation}\mspace{14mu} 12} \right) \\{N = \frac{R_{in} \times W}{E}} & \left( {{Equation}\mspace{14mu} 13} \right)\end{matrix}$

Note that equations 12 and 13 can lead to fractional values for thenumber of resources in the customer service organization N. In thecontext of personnel, a fractional number of resources can refer to aperson in the customer service organization who is allocated to the taskof processing service requests for a percentage of time that issubstantially equal to the fractional value of N. In the context ofprocessing resources, a fractional number of resources can refer to aprocessing resource in the customer service organization that isallocated to the task of processing service requests for a percentage oftime that is substantially equal to the fractional value of N. Inanother embodiment, N may be an integer, rather than a fractional value.

Upon determining the number of resources in the customer serviceorganization N, based upon the rate at which service requests arereceived R_(in), the amount of time per service request a resourcespends to process a service request W, and the efficiency factor E, theoperator of the customer service organization can compare N with theactual number of resources in the customer service organization N_(A).If:

N_(A)>N   (Equation 14)

the operator can reallocate resources away from processing servicerequests and to other tasks. On the other hand, if:

N_(A)<N   (Equation 15)

then the operator can allocate additional resources to the processing ofservice requests.

In a particular embodiment, the customer service organization canreallocate processing resources away from processing automated servicerequests, or can allocate additional processing resources to theprocessing of automated service requests based upon a determination ofthe amount of processing resources desired by the customer serviceorganization to satisfy a particular rate at which automated servicerequests are received, based upon the amount of time per automatedservice request a processing resource spends to process an automatedservice request, and the efficiency factor of the processing resource.When the determination of the amount of processing resources desired bythe customer service organization includes an integer, the customerservice organization can reduce or increase the amount of processingresources by an amount substantially equal to the integer. When thedetermination of the amount of processing resources desired by thecustomer service organization includes a fractional number, the customerservice organization can reduce or increase the amount of time aparticular processing resource is dedicated to processing automatedservice requests by an amount that is substantially equal to thefractional number. In this embodiment, the determination of the amountof processing resources desired by the customer service organization canbe the basis to automatically add or reduce the amount of processingresources in the customer service organization. For example, a serverfarm can automatically allocate additional servers to processingautomated service requests upon detecting an increase in the rate ofincoming automated service requests.

In another embodiment, the customer service organization can reallocatehuman resources away from processing personal service requests, or canallocate additional human resources to the processing of personalservice requests based upon a determination of the amount of humanresources desired by the customer service organization to satisfy aparticular rate at which personal service requests are received, basedupon the amount of time per personal service request a human resourcespends to process a personal service request, and the efficiency factorof the human resource. In this embodiment, the determination of thenumber of human resources desired by the customer service organizationcan be the basis for an action to hire or lay off personnel in thecustomer service organization.

FIG. 8 illustrates a method of allocating resources in a serviceorganization. A case load is determined for the service organization inblock 802. For example, the case load can be similar to the rate atwhich service requests are received R_(in) by customer serviceorganization 100, as described above. A work per case, including adegree of non-linearity per case is determined for the serviceorganization in block 804. For example, the work per case can be similarto the work per case of customer service organization 100, as describedabove, and can include determining a time per service request spentactually processing the service request, a time per service request thatis overhead, a time to list service requests, a time to open the servicerequest, a time to evaluate the service request, and a number ofincidents to fully process the service request (e.g., a non-linearityper case). An efficiency factor is determined for the serviceorganization in block 806. For example, the efficiency factor can besimilar to the efficiency factor of customer service organization 100,as described above.

The case load is multiplied by the work per case, and divided by theefficiency factor to determine a predicted resource count N in block808. A decision is made as to whether or not the predicted resourcecount N is equal to an actual resource count N_(A) in decision block810. If so, the “YES” branch of decision block 810 is taken, and themethod ends at block 812. If the predicted resource count N is not equalto the actual resource count N_(A), the “NO” branch of decision block810 is taken, and a decision is made as to whether or not the predictedresource count N is greater than the actual resource count N_(A) indecision block 814. If so, the “YES” branch of decision block 814 istaken, the actual resource count NA is reduced in block 816, and themethod ends at block 812. If the predicted resource count N is greaterthan the actual resource count N_(A), the “NO” branch of decision block814 is taken, the actual resource count NA is increased in block 818,and the method ends at block 812.

In a particular embodiment, an information handling system can be usedto carry out one or more of the previously described methods, in wholeor in part. In another embodiment, one or more of the systems describedabove can be implemented in the form of an information handling system.FIG. 9 illustrates a functional block diagram of an embodiment of aninformation handling system, generally designated as 900. Informationhandling system 900 includes processor 910, a chipset 920, a memory 930,a graphics interface 940, an input/output (I/O) interface 950, a diskcontroller 960, a network interface 970, and a disk emulator 980.

Processor 910 is coupled to chipset 920. Chipset 920 supports processor910, allowing processor 910 to process machine-executable code. In aparticular embodiment (not illustrated), information handling system 900includes one or more additional processors, and chipset 920 supports themultiple processors, allowing simultaneous processing by each of theprocessors, permitting the exchange of information between theprocessors and the other elements of information handling system 900.Processor 910 can be coupled to chipset 920 via a unique channel, or viaa bus that shares information between processor 910, chipset 920, andother elements of information handling system 900.

Memory 930 is coupled to chipset 920. Memory 930 can be coupled tochipset 920 via a unique channel, or via a bus that shares informationbetween chipset 920, memory 930, and other elements of informationhandling system 900. In particular, a bus can share information betweenprocessor 910, chipset 920 and memory 930. In a particular embodiment(not illustrated), processor 910 is coupled to memory 930 through aunique channel. In accordance with another aspect (not illustrated), aninformation handling system can include a separate memory dedicated toeach of the processors. A non-limiting example of memory 930 includesstatic, dynamic. Or non-volatile random access memory (SRAM, DRAM, orNVRAM), read only memory (ROM), flash memory, another type of memory, orany combination thereof.

Graphics interface 940 is coupled to chipset 920. Graphics interface 940can be coupled to chipset 920 via a unique channel, or via a bus thatshares information between chipset 920, graphics interface 940, andother elements of information handling system 900. Graphics interface940 is coupled to a video display 944. Other graphics interfaces (notillustrated) can also be used in addition to graphics interface 940 ifneeded or desired. Video display 944 can include one or more types ofvideo displays, such as a flat panel display or other type of displaydevice.

I/O interface 950 is coupled to chipset 920. I/O interface 950 can becoupled to chipset 920 via a unique channel, or via a bus that sharesinformation between chipset 920, I/O interface 950, and other elementsof information handling system 900. Other I/O interfaces (notillustrated) can also be used in addition to I/O interface 950 if neededor desired. I/O interface 950 is coupled to one or more add-on resources954. Add-on resource 954 can include a data storage system, a graphicsinterface, a network interface card (NIC), a sound/video processingcard, another suitable add-on resource or any combination thereof.

Network interface device 970 is coupled to I/O interface 950. Networkinterface 970 can be coupled to I/O interface 950 via a unique channel,or via a bus that shares information between I/O interface 950, networkinterface 970, and other elements of information handling system 900.Other network interfaces (not illustrated) can also be used in additionto network interface 970 if needed or desired. Network interface 970 canbe a network interface card (NIC) disposed within information handlingsystem 900, on a main circuit board (e.g., a baseboard, a motherboard,or any combination thereof), integrated onto another component such aschipset 920, in another suitable location, or any combination thereof.Network interface 970 includes a network channel 972 that provideinterfaces between information handling system 900 and other devices(not illustrated) that are external to information handling system 900.Network interface 970 can also include additional network channels (notillustrated).

Disk controller 960 is coupled to chipset 910. Disk controller 960 canbe coupled to chipset 920 via a unique channel, or via a bus that sharesinformation between chipset 920, disk controller 960, and other elementsof information handling system 900. Other disk controllers (notillustrated) can also be used in addition to disk controller 960 ifneeded or desired. Disk controller 960 can include a disk interface 962.Disk controller 960 can be coupled to one or more disk drives via diskinterface 962. Such disk drives include a hard disk drive (HDD) 964 oran optical disk drive (ODD) 966 (e.g., a Read/Write Compact Disk(R/W-CD), a Read/Write Digital Video Disk (R/W-DVD), a Read/Write miniDigital Video Disk (R/W mini-DVD), or another type of optical diskdrive), or any combination thereof. Additionally, disk controller 960can be coupled to disk emulator 980. Disk emulator 980 can permit asolid-state drive 984 to be coupled to information handling system 900via an external interface. The external interface can include industrystandard busses (e.g., USB or IEEE 1384 (Firewire)) or proprietarybusses, or any combination thereof. Alternatively, solid-state drive 984can be disposed within information handling system 900.

In a first aspect, a method includes determining a case load for anorganization where the case load includes a number of cases theorganization expects to process in a duration of time. The method alsoincludes determining a case rate for a work resource in the organizationwhere the case rate includes a number of cases that the work resourcecan process in the duration of time a particular case within a subset ofthe cases is processed non-linearly. The method further includesdetermining a resource demand prediction by dividing the case load bythe case rate, comparing the resource demand prediction to an actualresource allocation in the organization, and changing the actualresource allocation in response to comparing the resource demandprediction to the first actual resource allocation.

In an embodiment of the first aspect, the particular case is processedby the work resource in more than one incident. In a further embodiment,another particular case is processed by the work resource in oneincident. In another embodiment, determining the case rate for the workresource further includes determining an amount of time the workresource is available to work on cases, determining an average amount oftime per case that the work resource spends processing multiple cases,and dividing the amount of time by the duration of time and by theaverage amount of time per case. In yet another embodiment, determiningthe average amount of time per case includes averaging another amount oftime the work resource spends processing the particular cases. In stillanother embodiment, the average amount of time per case is determined asthe sum of an amount of time the work resource spends processing themultiple cases, and an amount of time the work resource spends preparingto work on the multiple cases. In a further embodiment, the amount oftime the work resource spends preparing to work on the multiple cases isdetermined as the average number of incidents to process the multiplecases, multiplied by the sum of an average amount of time per incidentto list the multiple cases, an average amount of time per incident toopen the multiple cases, and an average amount of time per incident toread the multiple cases.

In another embodiment of the first aspect, when the resource demandprediction is greater than the actual resource allocation, changing theactual resource allocation includes increasing the number of workresources. In another embodiment of the first aspect, when the resourcedemand prediction is less than the actual resource allocation, changingthe actual resource allocation includes decreasing the number of workresources.

In a second aspect, a memory for an information handling system hasmachine-executable code stored therein, and the machine-executable codeincludes instructions to carry out a method. The method includesdetermining a case load for an organization where the case load includesa number of cases the organization expects to process in a duration oftime. The method also includes determining a case rate for a workresource in the organization, where the case rate includes a number ofcases that the work resource can process in the duration of time, and aparticular case within a subset of the cases is processed non-linearly.The method further includes determining a resource demand prediction bydividing the case load by the case rate, comparing the resource demandprediction to an actual resource allocation in the organization, storinga recommended resource allocation that is based on the differencebetween the resource demand prediction and the actual resourceallocation in the memory, and changing the actual resource allocation inresponse to storing the recommended resource allocation.

In an embodiment of the second aspect, the particular case is processedby the work resource in more than one incident. In another embodiment,another particular case is processed by the work resource in oneincident. In still another embodiment, determining the case rate for thework resource includes determining an amount of time the work resourceis available to work on cases, determining an average amount of time percase that the work resource spends processing multiple cases wheredetermining the average amount of time per case includes averaging anamount of time the work resource spends processing the particular cases,and dividing the amount of time by the duration of time and by theaverage amount of time per case. In another embodiment, the averageamount of time per case is determined as the sum of another amount oftime the work resource spends processing the multiple of cases, andanother amount of time the work resource spends preparing to work on themultiple cases where the amount of time is determined as an averagenumber of incidents to process the multiple cases, multiplied by the sumof an average amount of time per incident to list the multiple cases, anamount of time per incident to open the multiple cases, and an averageamount of time per incident to read the multiple cases.

In another embodiment of the second aspect, when the recommendedresource allocation is greater than zero, changing the actual resourceallocation includes increasing the number of work resources. In yetanother embodiment of the second aspect, when the recommended resourceallocation is less than zero, changing the actual resource allocationincludes decreasing the number of work resources.

In a third aspect, an information handling system includes a memorydevice that includes machine-executable code stored therein, and aprocessor. The processor is operable to execute the machine-executablecode to determine a case load for an organization that includes a numberof cases the organization expects to process in a duration of time. Theprocessor is also operable to determine a case rate for a worker in theorganization where the case rate includes a number of cases that theworker can process in the duration of time and a particular case withina subset of the multiple cases is processed non-linearly. The processoris further operable to divide the case load by the case rate todetermine a headcount prediction, subtract the headcount prediction froman actual headcount in the organization to determine a recommendedheadcount, store the recommended headcount in the memory device, andreallocate a resource within the organization based upon the recommendedheadcount.

In an embodiment of the third aspect, the processor is further operableto determine an amount of time the worker is available to work on cases,determine an average amount of time per case that the worker spendsprocessing the multiple cases, and divide the amount of time by theduration of time and by the average amount of time per case. In anotherembodiment, the processor is further operable to sum another amount oftime the worker spends processing the multiple cases, and another amountof time the worker spends preparing to work on the multiple cases. Inyet another embodiment, the processor is further operable to multiply anaverage number of touches to process the multiple cases to the sum of anaverage amount of time per touch to list the multiple cases, an averageamount of time per touch to open the multiple cases, and an averageamount of time per touch to read the multiple cases.

For purposes of this disclosure, an information handling system caninclude any instrumentality or aggregate of instrumentalities operableto compute, classify, process, transmit, receive, retrieve, originate,switch, store, display, manifest, detect, record, reproduce, handle, oruse any form of information, intelligence, or data for business,scientific, control, entertainment, or other purposes. For example, aninformation handling system can be a personal computer, a personal dataassistant, a consumer electronic device (e.g., a portable music player,a portable DVD player, or a digital video recorder, etc.), a networkcommunication device (e.g., a server or server blade, a storage device,a switch/router, a wireless router, etc.), or any other suitable device,and can vary in size, shape, performance, functionality, and price. Aninformation handling system can also include a set of any of theforegoing devices.

Portions of an information handling system, when referred to as a“device”, a “module”, a “resource”, or the like, can be configured ashardware, firmware, software, or any combination thereof. A device, amodule, or a resource can be implemented in hardware. A non-limitingexample of a device, a module, or a resource implemented as hardwareincludes: an integrated circuit (e.g., an Application SpecificIntegrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), astructured ASIC, or a device embedded on a larger chip), a card (e.g., aPeripheral Component Interface (PCI) card, a PCI-Express (PCIe) card, aPersonal Computer Memory Card International Association (PCMCIA) card,or other such expansion card), or a system (e.g., a motherboard, asystem-on-a-chip (SoC), or a stand-alone device). Similarly, the device,a module, or a resource can be implemented in firmware (i.e., anysoftware running on an embedded device, a Pentium class or PowerPC™brand processor, or other such device) or in software (i.e., anysoftware capable of operating in the relevant environment). The device,module, or resource can also be implemented as a combination ofhardware, firmware, or software. Note that an information handlingsystem can include an integrated circuit or a board-level product havingportions thereof that can also be any combination of hardware, firmware,or software.

Devices, modules, resources, or programs that are in communication withone another need not be in continuous communication with each other,unless expressly specified otherwise. In addition, devices, modules,resources, or programs that are in communication with one another cancommunicate directly or indirectly through one or more intermediaries.

The embodiments discussed above describe, in part, distributed computingsolutions that manage all or part of a communicative interaction betweennetwork elements. A network element can be a node, a piece of hardware,software, firmware, middleware, another component of a computing system,or any combination thereof. In this context, a communicative interactioncan be intending to send information, sending information, requestinginformation, receiving information, receiving a request for information,or any combination thereof. As such, a communicative interaction couldbe unidirectional, bi-directional, multi-directional, or any combinationthereof. In some circumstances, a communicative interaction could berelatively complex and, involve two or more network elements. Forexample, a communicative interaction can be “a conversation,” or seriesof related communications between a client and a server—each networkelement sending and receiving information to and from the other.Whatever form the communicative interaction takes, the network elementsinvolved need not take any specific form.

Two or more information handling systems can be coupled together in anetwork such that individual information handling systems in thenetwork, referred to as nodes of the network, can exchange informationwith each other. A non-limiting example of a network includes a localarea network (LAN), a metropolitan area network (MAN), a storage areanetwork (SAN), a wide area network (WAN), a wireless local area network(WLAN), a virtual private network (VPN), an intranet, the Internet, anyother appropriate network architecture or system, or any combinationthereof. The nodes on a network can include storage devices, fileservers, print servers, personal computers, laptop computers, personaldata assistants, media content players, other devices capable of beingcoupled to a network, or any combination thereof.

In the description above, a flow-charted technique can be described in aseries of sequential actions. The sequence of the actions and the partyperforming the steps can be freely changed without departing from thescope of the teachings. Actions can be added, deleted, or altered inseveral ways. Similarly, the actions can be re-ordered or iterated.Further, although processes, methods, algorithms, or the like can bedescribed in a sequential order, such processes, methods, algorithms, orany combination thereof can be operable to be performed in alternativeorders. Further, some actions within a process, method, or algorithm canbe performed simultaneously during at least a point in time (e.g.,actions performed in parallel), can also be performed in whole, in part,or any combination thereof.

Note that not all of the activities described above in the generaldescription or the examples are required, that a portion of a specificactivity can not be required, and that one or more further activitiescan be performed, in addition to those described. Still further, theorder in which activities are listed are not necessarily the order inwhich they are performed.

The specification and illustrations of the embodiments described hereinare intended to provide a general understanding of the structure of thevarious embodiments. The specification and illustrations are notintended to serve as an exhaustive and comprehensive description of allof the elements and features of apparatus and systems that use thestructures or methods described herein. Many other embodiments can beapparent to those of skill in the art upon reviewing the disclosure.Other embodiments can be used and derived from the disclosure, such thata structural substitution, logical substitution, or another change canbe made without departing from the scope of the disclosure. Accordingly,the disclosure is to be regarded as illustrative rather thanrestrictive.

Certain features described herein in the context of separate embodimentsfor the sake of clarity, can also be provided in combination in a singleembodiment. Conversely, various features that are, for brevity,described in the context of a single embodiment, can also be providedseparately, or in any sub-combination. Further, reference to valuesstated in ranges includes each and every value within that range.

Benefits, other advantages, and solutions to problems have beendescribed above with regard to specific embodiments. However, thebenefits, advantages, solutions to problems, and any feature(s) that cancause any benefit, advantage, or solution to occur, or become morepronounced are not to be construed as a critical, required, or essentialfeature of any or all the claims.

The above-disclosed subject matter is to be considered illustrative, andnot restrictive, and the appended claims are intended to cover any andall such modifications, enhancements, and other embodiments that fallwithin the scope of the present invention. Thus, to the maximum extentallowed by law, the scope of the present invention is to be determinedby the broadest permissible interpretation of the following claims andtheir equivalents, and shall not be restricted or limited by theforegoing detailed description.

1. A method comprising: determining a case load for an organization,wherein the case load includes a number of cases the organizationexpects to process in a duration of time; determining a case rate for awork resource in the organization, wherein: the case rate includes anumber of cases that the work resource can process in the duration oftime; and a first particular case within a subset of a plurality ofcases is processed non-linearly; determining a resource demandprediction by dividing the case load by the case rate; comparing theresource demand prediction to an actual resource allocation in theorganization; and in response to comparing the resource demandprediction to the first actual resource allocation, changing the actualresource allocation.
 2. The method of claim 1, wherein the firstparticular case is processed by the work resource in more than oneincident.
 3. The method of claim 2, wherein a second particular case isprocessed by the work resource in one incident.
 4. The method of claim3, wherein determining the case rate for the work resource furthercomprises: determining a first amount of time the work resource isavailable to work on cases; determining a first average amount of timeper case that the work resource spends processing the plurality ofcases; and dividing the first amount of time by the duration of time andby the first average amount of time per case.
 5. The method of claim 4,wherein determining the first average amount of time per case includesaveraging a second amount of time the work resource spends processing:the first particular case; and the second particular case.
 6. The methodof claim 5, wherein the first average amount of time per case isdetermined as the sum of: a third amount of time the work resourcespends processing the plurality of cases; and a fourth amount of timethe work resource spends preparing to work on the plurality of cases. 7.The method of claim 6, wherein the fourth amount of time is determinedas: an average number of incidents to process the plurality of cases,multiplied by; the sum of: a second average amount of time per incidentto list the plurality of cases; a third average amount of time perincident to open the plurality of cases; and a fourth average amount oftime per incident to read the plurality of cases.
 8. The method of claim1, wherein, when the resource demand prediction is greater than theactual resource allocation, changing the actual resource allocationincludes increasing the number of work resources.
 9. The method of claim1, wherein, when the resource demand prediction is less than the actualresource allocation, changing the actual resource allocation includesdecreasing the number of work resources.
 10. A memory for an informationhandling system, wherein the memory has machine-executable code storedtherein, and wherein the machine-executable code includes instructionsfor carrying out a method comprising: determining a case load for anorganization, wherein the case load includes a number of cases theorganization expects to process in a duration of time; determining acase rate for a work resource in the organization, wherein: the caserate includes a number of cases that the work resource can process inthe duration of time; and a first particular case within a subset of aplurality of cases is processed non-linearly; determining a resourcedemand prediction by dividing the case load by the case rate; comparingthe resource demand prediction to an actual resource allocation in theorganization; in response to comparing the resource demand prediction tothe actual resource allocation in the organization, storing arecommended resource allocation in the memory, wherein the recommendedresource allocation is based on the difference between the resourcedemand prediction and the actual resource allocation; and in response tostoring the recommended resource allocation, changing the actualresource allocation.
 11. The memory of claim 10, wherein the firstparticular case is processed by the work resource in more than oneincident.
 12. The memory of claim 11, wherein a second particular caseis processed by the work resource in one incident.
 13. The method ofclaim 12, wherein determining the case rate for the work resourcefurther comprises: determining a first amount of time the work resourceis available to work on cases; determining a first average amount oftime per case that the work resource spends processing the plurality ofcases, wherein determining the first average amount of time per caseincludes averaging a second amount of time the work resource spendsprocessing: the first particular case; and the second particular case;and dividing the first amount of time by the duration of time and by thefirst average amount of time per case.
 14. The memory of claim 13,wherein the first average amount of time per case is determined as thesum of: a third amount of time the work resource spends processing theplurality of cases; and a fourth amount of time the work resource spendspreparing to work on the plurality of cases, wherein the fourth amountof time is determined as: an average number of incidents to process theplurality of cases, multiplied by; the sum of: a second average amountof time per incident to list the plurality of cases; a third averageamount of time per incident to open the plurality of cases; and a fourthaverage amount of time per incident to read the plurality of cases. 15.The memory of claim 10, wherein, when the recommended resourceallocation is greater than zero, changing the actual resource allocationincludes increasing the number of work resources.
 16. The memory ofclaim 10, wherein, when the recommended resource allocation is less thanzero, changing the actual resource allocation includes decreasing thenumber of work resources.
 17. An information handling system comprising:a memory device having machine-executable code stored therein; and aprocessor operable to execute the machine-executable code to: determinea case load for an organization, wherein the case load includes a numberof cases the organization expects to process in a duration of time;determine a case rate for a worker in the organization, wherein: thecase rate includes a number of cases that the worker can process in theduration of time; and a first particular case within a subset of aplurality of cases is processed non-linearly; divide the case load bythe case rate to determine a headcount prediction; subtract theheadcount prediction from an actual headcount in the organization todetermine a recommended headcount; store the recommended headcount inthe memory device; and reallocate a resource within the organizationbased upon the recommended headcount.
 18. The information handlingsystem of claim 17, wherein, in determining the case rate for theworker, the processor is further operable to: determine a first amountof time the worker is available to work on cases; determine an averageamount of time per case that the worker spends processing the pluralityof cases; and divide the first amount of time by the duration of timeand by the average amount of time per case.
 19. The information handlingsystem of claim 18, wherein, in determining the average amount of timeper case that the worker spends processing the plurality of cases, theprocessor is further operable to sum: a second amount of time the workerspends processing the plurality of cases; and a third amount of time theworker spends preparing to work on the plurality of cases.
 20. Theinformation handling system of claim 18, wherein, in determining thethird amount of time, the processor is further operable to: multiply afirst average number of touches to process the plurality of cases to;the sum of: a second average amount of time per touch to list theplurality of cases; a third average amount of time per touch to open theplurality of cases; and a fourth average amount of time per touch toread the plurality of cases.